Example: Parametric Bootstrap estimate of the mean of a Normal distribution with known standard deviation


Imagine that we wish to estimate the true depth of a well using some sort of sonic probe. The probe has a known standard error s = 0.2 metres i.e. s is the standard deviation of the normally distributed variation of results the probe will produce when repetitively measuring the same depth. In order to estimate this depth we take n separate measurements. These measurements have a mean of  metres. The parametric Bootstrap model would take the average of n Normal(, s) distributions to estimate the true mean m of the distribution of possible measurement results, i.e. the true well depth. From Central Limit Theorem, we know that this calculation is equivalent to:

which is the standard classical statistics equation in this situation.

 

See Also

 

ModelRisk

Monte Carlo simulation in Excel. Learn more

Tamara

Adding risk and uncertainty to your project schedule. Learn more

Navigation

FREE MONTE CARLO SIMULATION SOFTWARE

For Microsoft Excel

Download your free copy of ModelRisk Basic today. Professional quality risk modeling software and no catches

Download ModelRisk Basic now

FREE PROJECT RISK SOFTWARE

For Primavera & Microsoft Project

Download your free copy of Tamara Basic today. Professional quality project risk software and no catches.

Download Tamara Basic now
-->